Topic Detection and Tracking for News Web Pages

This paper proposes a new approach to observe, summarize and track events from a collection of news Web pages. Given a set of temporal Web pages, we obtain valid times-tamp from Web pages and detect events by means of clustering. Then we track events by using KeyGraph based on the clusters and abstract the clusters by using SuffixTree. We examine some experimental results and show the usefulness of our approach

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